Vaishnavi Lolla
Jersey City,NJ
Summary
Results-driven Data Engineer with 5+ years of experience designing, building, and optimizing data pipelines and cloud-based analytics platforms. Proven expertise in big data frameworks (Spark, Kafka), cloud ecosystems (GCP, AWS, Azure), and modern ETL tools. Adept at driving performance improvements, enabling real-time data insights, and deploying scalable infrastructure using Terraform and CI/CD practices. Passionate about delivering secure, reliable, and governed data solutions across healthcare and finance domains.
Overview
5
5
years of professional experience
Work History
Data Engineer
UnitedHealth Group
Minnesota
11.2024 - Current
- Developed scalable data pipelines using GCP Dataflow and BigQuery for healthcare analytics.
- Processed large volumes of EHRs with Apache Beam and PySpark to ensure performance and scalability.
- Designed and implemented FHIR-compliant data models to support interoperability standards.
- Secured data storage using GCS and IAM roles for granular access control.
- Automated ETL workflows using Cloud Composer (managed Apache Airflow).
- Built interactive dashboards in Looker to enable real-time clinical decision-making.
- Applied data anonymization techniques to comply with HIPAA and GDPR standards.
- Tuned BigQuery queries for cost-optimized and efficient analytics reporting.
- Integrated ML models for predictive analytics in patient care scenarios.
- Implemented CI/CD with Cloud Build and Terraform for infrastructure automation.
- Collaborated with compliance teams to align data practices with federal health laws.
- Documented pipeline designs and maintained high test coverage for reliability.
- Created audit logs and metadata catalogs for traceability and governance.
- Led onboarding and mentorship for new team members on cloud data tooling.
- Tech Stack: GCP (Dataflow, BigQuery, Cloud Composer, GCS, IAM), Apache Beam, PySpark, Looker, Terraform, FHIR.
Data Engineer
HP
Palo Alto, CA
08.2023 - 09.2024
- Developed scalable ETL pipelines, improving ingestion efficiency by 35%.
- Built real-time data streaming using Kafka and Spark Streaming for e-prescription systems.
- Utilized AWS S3 and Athena for data lake construction and efficient querying.
- Migrated legacy Oracle data to cloud-based architecture to reduce storage costs.
- Containerized data solutions with Docker and EKS for scalable deployment.
- Established DevOps pipelines with AWS CodePipeline and Terraform for CI/CD.
- Optimized Snowflake with partitioning and indexing for better performance.
- Implemented fraud detection analytics using complex SQL and stored procedures.
- Integrated Tableau dashboards for instant business insights.
- Processed semi-structured data using Delta Lake on Databricks.
- Ensured security via AWS IAM and encrypted communication across services.
- Improved Spark performance through tuning and resource optimization.
- Developed SOAP-based web services for cross-platform data exchange.
- Mentored engineers and enhanced productivity through reusable frameworks.
- Tech Stack: AWS (S3, Athena, CodePipeline, IAM), Kafka, Spark, Snowflake, Tableau, Docker, EKS, Terraform, Delta Lake, SOAP, Databricks.
Data Engineer
Cognizant Technology Solutions
Dallas-Fort Worth, TX
03.2020 - 06.2023
- Engineered end-to-end data pipelines, reducing processing time by 60%.
- Utilized Talend for ETL operations and integration from various sources.
- Migrated legacy ETL workflows to Snowflake to modernize data platforms.
- Designed serverless data workflows for cost-effective scalability.
- Built dashboards to enable real-time tracking of investment portfolios.
- Deployed machine learning models in Python for credit risk analytics.
- Developed Azure Data Lake storage solutions for financial data lakes.
- Authored optimized PL/SQL and T-SQL scripts for transformations.
- Integrated Apache Kafka for real-time transaction monitoring.
- Implemented data lineage tracking with Azure Purview for compliance.
- Used Terraform and Kubernetes for containerized data service deployment.
- Performed code reviews to reduce technical debt and enhance quality.
- Documented and standardized ETL frameworks and monitoring procedures.
- Collaborated with QA for automated testing and validation of pipelines.
- Tech Stack: Talend, Snowflake, Azure Data Lake, Azure Purview, PL/SQL, T-SQL, Kafka, Terraform, Kubernetes, Python.
Education
Master of Science - Computer Science
Montclair State University
Montclair, NJ05-2025
Skills
Cloud platforms: Google Cloud, AWS, Microsoft Azure
Programming languages: Python, SQL, PySpark
Big data technologies: Apache Spark, Kafka, Beam
ETL tools: Talend, Snowflake, Databricks
DevOps tools: Terraform, Docker, Kubernetes
BI tools: Looker, Tableau
Data governance: IAM compliance, HIPAA/GDPR
Interoperability standards: FHIR, SOAP/REST APIs
Key Achievements
- Built and optimized scalable data pipelines across cloud platforms (GCP, AWS, Azure), improving data processing speed by up to 60% and reducing infrastructure costs by 25%.
- Delivered real-time analytics solutions using tools like BigQuery, Spark, Kafka, and Tableau/Looker, enabling faster decision-making in healthcare and financial domains.
- Integrated machine learning models for use cases like fraud detection and credit risk analysis, resulting in up to 40% improvement in model accuracy and detection efficiency.
- Strengthened data governance and security by implementing HIPAA/GDPR compliance, IAM policies, and data lineage tracking with tools like Azure Purview and Terraform.
Timeline
Data Engineer
UnitedHealth Group
11.2024 - Current
Data Engineer
HP
08.2023 - 09.2024
Data Engineer
Cognizant Technology Solutions
03.2020 - 06.2023
Master of Science - Computer Science
Montclair State University
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